Pirsch Analytics vs June
Side-by-side trajectory, velocity, and editorial themes.
Pirsch ships a tight maintenance cadence — bot filtering, dashboard polish, and dependency hygiene.
Pirsch is releasing every few days with very small payloads. The April cluster centers on bot detection — improved filters in 2.14.10 and 2.14.12, plus a referrer-parameter bot fix in 2.14.11. March added dashboard creation settings, an option to hide the UTM panel, expiration times on access links, and a referrer blacklist update. Earlier in February, email reports gained a start date and the Fathom Analytics importer was updated.
Pirsch is in steady operational mode — defending against bots, polishing dashboard surfaces, and keeping dependencies current. The Fathom importer updates and email-report work are the only signs of growth-oriented investment; otherwise the cadence is custodial. The product feels like it's competing on reliability and privacy rather than feature surface.
Expect bot-filter work to continue (this is an arms race for any analytics provider) and the Fathom importer to keep getting attention as Fathom users churn. Larger directional moves aren't visible in the feed; the next signal would be a real new product surface — funnels v2, server-side eventing, or an AI insights panel.
June's last visible push was a tight May 2025 B2B sprint — Custom Objects, SQL traits, PostHog integration.
June is product analytics for B2B SaaS, and the only visible release activity in the input is a concentrated four-week sprint in May 2025: SQL computed traits, PostHog as a data source, increased computed-trait limits, and the GA of Custom Objects after a two-month rollout. Each release is paired with small fixes (Slack alerts, HubSpot reverse sync) suggesting a stable maintenance cadence around the headline launches.
The May 2025 batch is internally consistent: every release widens what June can model (Custom Objects), how flexibly customers can compute on it (SQL traits), or how easily it slots into existing data plumbing (PostHog source). All three target the B2B-SaaS persona that wants more than user/account analytics. After this burst the changelog goes quiet in the input — it's not clear from the entries alone whether the product moved to a slower cadence, switched publishing channels, or paused.
The entries don't support a confident prediction about what comes next. If publishing resumes from the same direction, the obvious extensions are deeper integrations with reverse-ETL or warehouse-native sources and richer pre-built health-score templates on top of SQL computed traits.
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